Satellite signal based positioning technologies, which are mainly used outdoors, are usually not suited to deliver a satisfactory performance when used for indoor positioning, since satellite signals of global navigation satellite systems (GNSS), like the global positioning system (GPS), do not penetrate through walls and roofs strongly enough for an adequate signal reception indoors. Thus, these positioning technologies are not able to deliver a performance indoors that would enable seamless, equal and accurate navigation experience outdoors and indoors.
Therefore, several dedicated solutions for indoor positioning have been developed and commercially deployed during the past years. Examples comprise solutions that are based on pseudolites, which are ground based GPS-like short-range beacons, ultra-sound positioning solutions, Bluetooth low energy (BLE) based positioning solutions, cellular network based positioning solutions and wireless local area network (WLAN) based positioning solutions.
A Bluetooth based positioning solution such as a self-contained positioning system, for instance, may be divided in at least three stages, an installation stage, a training stage and a positioning stage.
In the installation stage, Bluetooth beacons are installed in the environment for which a positioning solution is to be provided.
In the subsequent training stage, learning data are collected. The data may be collected in the form of radio fingerprint observation reports that are based on measurements by mobile devices. A radio fingerprint observation report may indicate a position estimate and measurements taken from the radio interface. The position estimate may be for example GNSS based, sensor-based, or manually inputted. Measurements taken from the radio interface may comprise, by way of example, measured radio signal strengths and an identifier of Bluetooth beacons transmitting the radio signals. The training may be a continuous background process, in which mobile devices of a large number of consumers are continuously reporting collected fingerprint observation reports to a server. Consumers may consent to a participation in such a radio fingerprint observation report collection, if their device is equipped with the needed functionality. This approach is also referred to as crowd-sourcing. Alternatively or in addition, mobile devices may be used for collecting radio fingerprint observation reports in a systematic manner. Collected fingerprint data may be uploaded to a database in a radio positioning server or in the radio positioning cloud, where algorithms may be run to generate radio coverage area models of Bluetooth beacons and/or radio positioning maps for positioning purposes.
In the positioning stage, a mobile device may estimate its current position based on own measurements taken from the radio interface and on the data or a subset of data that is available from the training stage. Coverage area model data or radio positioning map data that has been generated in the training stage may be transferred to mobile devices by a radio positioning server via the Internet as assistance data for use in position determinations. Alternatively, coverage area model data and/or radio positioning map data may be stored in a radio positioning server to which the mobile devices may connect to via the Internet for obtaining a position estimate.
A similar approach could be used for a positioning that is based on other types of terrestrial transmitters or on a combination of different types of terrestrial transmitters.